{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# -*-coding:utf-8-*-\n",
    "\n",
    "import pandas as pd     \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "# x = np.random.randn(0, 100, 1)\n",
    "x = np.linspace(-np.pi*3, 3*np.pi)\n",
    "y1 = np.sin(x)+np.pi*0.5-np.cos(x)\n",
    "y2 = np.sin(x)-np.cos(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6HcXZbDbyt64mwjNAvAV9DbVKTVpADGfrymkpLVY6HbuQv301Oq2Osd7iOMzX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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x270e820d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.9848282275 1.0\n"
     ]
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,6))\n",
    "# ax.set_visible(ax.spines['right']=False)\n",
    "fig.dpi = 72\n",
    "ax.spines['left'].set_position('center')\n",
    "ax.spines['bottom'].set_position('center')\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "# ax.set_yticks([0,1,2,3])\n",
    "# ax.set_yticklabels([0,1,2,3])\n",
    "ax.set_ylim(-4,4)\n",
    "ax.set_xlim(-10,10)\n",
    "ax.plot(x,y1,'k',label=r'$\\sin(x)$+0.5*$\\pi$-$\\cos(x)$')\n",
    "ax.plot(x,y2,'k',label=r'$\\sin(x)$-$\\cos(x)$')\n",
    "ax.axvline(x = -np.pi*3,ymin=0.62,ymax=0.82,color='k')\n",
    "ax.axvline(np.pi*3,ymin=0.62,ymax=0.82,color='k')\n",
    "# ax.axhline(y1.max(),color='m')\n",
    "ax.axhspan(-1.5,3,0.028,0.97,alpha=0.5)\n",
    "# ax.legend()\n",
    "# ax.set_xticks([-6,-4,-2,0,2,4,6])\n",
    "# ax.set_xticklabels([r'-3$\\pi$', r'-2$\\pi$',  r'-$\\pi$', '0', r'$\\pi$', r'2$\\pi$',r'3$\\pi$'])\n",
    "# ax.set_title('y1 = $\\sin(x)$+0.5*$\\pi$-$\\cos(x)$\\ny2 = $\\sin(x)$-$\\cos(x)$' )\n",
    "ax.fill_between(x,y2,y1,color='r')\n",
    "plt.show()\n",
    "print(y1.max(),y2[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method draw in module matplotlib.artist:\n",
      "\n",
      "draw(renderer, *args, **kwargs) method of matplotlib.axes._subplots.AxesSubplot instance\n",
      "    Draw everything (plot lines, axes, labels)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ax.acorr(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Histogram of IQ: $\\mu=9.187$, $\\sigma=0.11$\n"
     ]
    }
   ],
   "source": [
    "print(r'Histogram of IQ: $\\mu=9.187$, $\\sigma=0.11$')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
